spkGNN: Genes Needed to Detect N True Positives

In mccallm/spkTools: Methods for Spike-in Arrays

Description

Computes the number of genes one would need to consider to obtain a given number of truly positive genes if one considered genes in order of decreasing observed fold change.

Usage

spkGNN(n, n.expr, n.unexpr, AccuracySlope, AccuracySD, nullfc)

Arguments

n	the desired number of true positives
n.expr	the actual number of truly expressed genes
n.unexpr	the actual number of truly unexpressed genes
AccuracySlope	the signal detect slope from the spkSlope function
AccuracySD	the standard deviation of the signal detect slope from the spkAccSD function
nullfc	a vector of null fold changes from the spkBox function

Value

This function returns the expected number of genes one would have to consider to obtain N true positives under the given conditions.

Author(s)

Matthew N. McCall

Examples

data(affy)
spkSlopeOut <- spkSlope(affy)
spkBoxOut <- spkBox(affy, spkSlopeOut, fc=2)
AccuracySlope <- round(spkSlopeOut$slope[-1], digits=2)
AccuracySD <- round(spkAccSD(affy, spkSlopeOut), digits=2)
spkGNN(n=25, n.expr=100, n.unexpr=10000, AccuracySlope[2],
AccuracySD[2], spkBoxOut[[2]])

mccallm/spkTools documentation built on May 7, 2019, 1:26 p.m.